The demand for job skills related to data processing -- NoSQL, Apache Hadoop, Python, and a smattering of other such skills -- has hit all-time highs, according to statistics collected by tech job site Dice.com. The biggest gains, though, are for all things NoSQL.

Dice claims the number of job postings for "NoSQL experts" -- those with experience in unstructured data systems like MongoDB -- has risen 54 percent since last year. Other, related skills, such as Apache Hadoop and Python, have also posted significant year-over-year gains (43 percent and 16 percent, respectively). Python has become one of the big go-to languages for data processing, thanks to its simplicity and its wide selection of data-processing libraries.

Indeed.com and its Job Trends graph provide more details about which big data skills were most in demand. Indeed.com's stats show MongoDB is the most commonly mentioned of the NoSQL variants in job listings, with 4,979 entries as of this writing. Couchbase, Redis, and CouchDB are the three next most common NoSQL variants, with Riak, Hbase, Neo4j, and ElasticSearch all trailing far behind.

When comparing MongoDB, Python, and Hadoop, Python is by far the most in-demand of the three, with some 27,000 jobs. However, Python developer jobs cover a great deal more than just big data, as expertise in Python can be applied to a broader range of jobs than MongoDB and Hadoop.

That said, the more analytics-related skills appear to command slightly higher pay. Indeed.com estimates that the majority of MongoDB jobs start somewhere north of $60,000, while with Python and Hadoop the majority of the pay is in the $50,000 and up range.

Other, more generic job requests related to big data are also up, with the term "big data" showing a major surge in appearances -- up 46 percent year-over-year. Generic requests for expertise in SaaS and cloud are also up, by 20 percent and 27 percent, respectively. Dice claims one side effect of a rise in cloud-based analytics is a growing demand for employees with multiple skills in this category -- for example, both Hadoop and cloud storage.

Michael Rappa, creator of the first academic program devoted to data analytics, made a similar observation when InfoWorld spoke to him about big data jobs in 2012. Rappa's take at the time was that big data wasn't "a new specialty or suite of tools we have to train people into," but rather a "new organizational reality that everyone will need to adjust to occupationally," where multiple occupations across an organization would require new awareness of how to work with big data.